Artificial Intelligence Driven Nuclear Reactor Instrumentation and Control Measurements In-core and Out-core in Nuclear Power Plants

Bahman Zohuri, Rahele Zadfathollah
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Abstract

The use of Artificial Intelligence (AI) in nuclear in-core instrumentation and control has the potential to improve the safety and efficiency of nuclear power plants. In-core instrumentation refers to the sensors and other measurement devices that are used to monitor the conditions inside the nuclear reactor core, such as temperature, pressure, and neutron flux. These measurements are used to control the operation of the reactor and ensure that it is operating within safe limits from Probabilistic Risk Assessment (PRA) point of view. One way that AI can be used in nuclear in-core and out-core Instrumentation and Control (I&C) as well as Instrumentation and Measurement (I&M) is by analyzing the data from these sensors in real-time and using machine learning algorithms to identify patterns and trends. This can help operators to detect potential problems or anomalies before they become critical, allowing them to take proactive measures to prevent accidents or malfunctions. AI can also be used to optimize the operation of the reactor by analyzing data from past operations and using this information to develop more efficient control strategies. For example, AI algorithms could be used to identify the most effective combination of control parameters to maintain a stable and safe reactor operation, while minimizing the use of fuel and other resources. Overall, the use of AI in nuclear In-core instrumentation and control has the potential to improve the safety, efficiency, and reliability of nuclear power plants. As AI technology continues to advance, we can expect to see more widespread adoption of these technologies in the nuclear industry
核电站堆芯内外人工智能驱动的核反应堆仪表与控制测量
人工智能(AI)在核堆芯仪表和控制中的应用有可能提高核电站的安全性和效率。堆芯内仪器是指用于监测核反应堆堆芯内部情况的传感器和其他测量设备,如温度、压力和中子通量。这些测量用于控制反应堆的运行,并从概率风险评估(PRA)的角度确保其在安全范围内运行。人工智能可以用于核内和核外仪器与控制(I&C)以及仪器与测量(I&M)的一种方法是实时分析来自这些传感器的数据,并使用机器学习算法来识别模式和趋势。这可以帮助作业者在问题变得严重之前发现潜在的问题或异常,使他们能够采取积极的措施来防止事故或故障。人工智能还可以通过分析过去运行的数据,并利用这些信息制定更有效的控制策略,来优化反应堆的运行。例如,人工智能算法可用于识别控制参数的最有效组合,以保持稳定和安全的反应堆运行,同时最大限度地减少燃料和其他资源的使用。总的来说,在核堆芯仪表和控制中使用人工智能有可能提高核电站的安全性、效率和可靠性。随着人工智能技术的不断进步,我们可以期待这些技术在核工业中得到更广泛的应用
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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